The present invention relates generally to aircraft-based and satellite-based imaging systems, and more particularly, to a system and method for computing the degree of translational offset between corresponding blocks extracted from images acquired by different sensors so that the images can be spatially registered.
The assignee of the present invention has developed and deployed a digital image processing system that registers images acquired under different conditions and using different types of sensors (e.g., electro-optical camera and synthetic aperture radar). This accurate pixel-to-pixel registration improves the exploitation of such imagery in three ways:
It makes it possible to detect changes in reconnaissance imagery acquired at two different times. It improves the Image Analyst""s ability to interpret the imagery by viewing the ground scene in two different spectral bands (e.g., visible and microwave).
It makes it possible to determine the exact location of objects detected in reconnaissance imagery by transferring them to reference imagery that has been very accurately referenced to the earth.
In order to properly exploit images acquired by different sensors, the two images must be registered to each other. One prior art technique to perform this image registration is disclosed in U.S. Pat. No. 5,550,937 entitled xe2x80x9cMechanism for Registering Digital Images Obtained from Multiple Sensors Having Diverse Image Collection Geometriesxe2x80x9d, issued Aug. 27, 1996.
In the known prior art disclosed in U.S. Pat. No. 5,550,937, methods for matching image blocks using image gradient magnitude information have been developed that work well with two images acquired with the same type of sensor (e.g., radar for both or electro-optical for both). However, heretofore, no method has been developed that uses a fast Fourier transform (for speed) and also makes use of both gradient magnitude and phase (direction) information to reliably and robustly spatially register the images from two different types of sensors.
Accordingly, it is an objective of the present invention to provide for a system and method for computing the degree of translational offset between corresponding blocks extracted from images acquired by different sensors so that the images can be spatially registered.
To accomplish the above and other objectives, the present invention provides for a system and method that computes the degree of translational offset between corresponding blocks extracted from images acquired by two sensors, such as electro-optic, infrared sensors, and radar for example, so that the images can be spatially registered. The present invention uses fast Fourier transform (FFT) correlation to provide for speed, and also uses gradient magnitude and phase (direction) information to provide for reliability and robustness.
In the present invention, two potentially dissimilar images acquired by two potentially different sensors, such as a synthetic aperature radar (SAR) and a visible band camera, for example, are resampled to a common resolution and orientation using image acquisition parameters provided with the imagery. The present invention provides an efficient robust mechanism for computing the degree of translational offset between corresponding blocks extracted from the two resampled images so that they can be spatially registered.
The present system and method matches image blocks extracted from the two resampled images and makes use of the intensity gradient of both images that are matched. The two points of novelty implemented in the present invention are that both gradient magnitude and phase (direction) information are used by the matching mechanism to improve the robustness and reliability of the matching results, and the matching mechanism uses a fast Fourier transform (FFF) so it can quickly match large image blocks even on a small personal computer.
The matching mechanism has several advantages over the prior art disclosed in U.S. Pat. No. 5,550,937. The present invention combines both gradient magnitude and phase information so that image structure is automatically and implicitly taken into account by the matcher. The present invention performs magnitude normalization so that the relative differences in intensity bias and gain between image blocks are ignored by the matcher. This normalization also makes the algorithm insensitive to spatial nonstationarity of edges (i.e., varying number of detailed features within each subarea) within the scene. The present invention makes use of the fast Fourier transform (FFT) so that matching results can be computed very rapidly even on a small personal computer.